code: def test_regression_with_categorical_training(self, mock_handler):
      # dataset, string values
      df = pd.DataFrame(range(1, 50), columns=["a"])
      df["b"] = 50 - df.a
      df["c"] = round((df["a"] * 3 + df["b"]) / 50)
      df["d"] = np.where(df.index % 2, "even", "odd")
  
      self.set_handler(mock_handler, name="pg", tables={"df": df})
  
      # create project
      self.run_sql("create database proj")
  
      # create predictor
      self.run_sql(
          """
             create model proj.modelx
             from pg (select * from df)
             predict c
             using
               engine='autokeras',
               train_time=0.01
          """
      )
      self.wait_predictor("proj", "modelx")
  
      # run predict
      ret = self.run_sql(
          """
             SELECT c
             FROM proj.modelx
             WHERE a=1 AND b=25 AND d="odd"
          """
      )
      avg_c = pd.to_numeric(ret.c).mean()
      assert (avg_c > -5) and (avg_c < 5)
  
file_path: mindsdb/tests/unit/ml_handlers/test_autokeras.py
imports: import time
  from unittest.mock import patch
  import pandas
  import numpy
  from mindsdb_sql import parse_sql
  from mindsdb.integrations.handlers.autokeras_handler.autokeras_handler import format_categorical_preds
  from tests.unit.executor_test_base import BaseExecutorTest
label_desc: Use image node_id 4 for calling the TestAutokeras obj's underlying member method code with example usage: obj.test_regression_with_categorical_training(mock_handler) without return types